Technical Program

MLSP-L3: Deep Learning II

Session Type: Lecture
Time: Wednesday, March 8, 08:30 - 10:30
Location: Grand Salon 3
Session Chair: David J. Miller, The Pennsylvania State University
 
MLSP-L3.1: PART-LEVEL FULLY CONVOLUTIONAL NETWORKS FOR PEDESTRIAN DETECTION
         Xinran Wang; Xidian University
         Cheolkon Jung; Xidian University
         Alfred O. Hero; University of Michigan
 
MLSP-L3.2: LEARNING TO INVERT: SIGNAL RECOVERY VIA DEEP CONVOLUTIONAL NETWORKS
         Ali Mousavi; Rice University
         Richard Baraniuk; Rice University
 
MLSP-L3.3: STRUCTURED DROPOUT FOR WEAK LABEL AND MULTI-INSTANCE LEARNING AND ITS APPLICATION TO SCORE-INFORMED SOURCE SEPARATION
         Sebastian Ewert; Queen Mary University of London
         Mark B. Sandler; Queen Mary University of London
 
MLSP-L3.4: HARNESSING NEURAL NETWORKS: A RANDOM MATRIX APPROACH
         Cosme Louart; CentraleSup√©lec
         Romain Couillet; CentraleSup√©lec
 
MLSP-L3.5: TRAINING VARIANCE AND PERFORMANCE EVALUATION OF NEURAL NETWORKS IN SPEECH
         Ewout van den Berg; IBM Watson Group
         Bhuvana Ramabhadran; IBM Watson Group
         Michael Picheny; IBM Watson Group
 
MLSP-L3.6: A DEEP LEARNING APPROACH TO MULTIPLE KERNEL FUSION
         Huan Song; Arizona State University
         Jayaraman J. Thiagarajan; Lawrence Livermore National Labs
         Prasanna Sattigeri; IBM T.J. Watson Research Center
         Karthikeyan Natesan Ramamurthy; IBM T.J. Watson Research Center
         Andreas Spanias; Arizona State University